Selection of head and neck cancer patients for adaptive radiotherapy to decrease xerostomia. Issue 1 (July 2016)

• Record Type: Journal Article
• Authors: Brouwer, Charlotte L.; Steenbakkers, Roel J.H.M.; van der Schaaf, Arjen; Sopacua, Chantal T.C.; van Dijk, Lisanne V.; Kierkels, Roel G.J.; Bijl, Hendrik P.; Burgerhof, Johannes G.M.; Langendijk, Johannes A.; Sijtsema, Nanna M.
• Is Part Of: Radiotherapy and oncology. Volume 120:Issue 1(2016:Jul.)
• Page Start: 36
• Page End: 40
• Publication Date: 2016-07
• Subjects: Head and neck -- Parotid glands -- Dosimetric changes -- Adaptive radiotherapy -- Patient selection -- Xerostomia; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2016.05.025
• Languages: English
• ISSNs: 0167-8140

Abstract

Abstract: Background and purpose: The aim of this study was to develop and validate a method to select head and neck cancer patients for adaptive radiotherapy (ART) pre-treatment. Potential pre-treatment selection criteria presented in recent literature were included in the analysis. Materials and methods: Deviations from the planned parotid gland mean dose (PG ΔDmean) were estimated for 113 head and neck cancer patients by re-calculating plans on repeat CT scans. Uni- and multivariable linear regression analyses were performed to select pre-treatment parameters, and ROC curve analysis was used to determine cut off values, for selecting patients with a PG dose deviation larger than 3 Gy. The patient selection method was validated in a second patient cohort of 43 patients. Results: After multivariable analysis, the planned PG Dmean remained the only significant parameter for PG ΔDmean. A sensitivity of 91% and 80% could be obtained using a threshold of PG Dmean of 22.2 Gy, for the development and validation cohorts, respectively. This would spare 38% (development cohort) and 24% (validation cohort) of patients from the labour-intensive ART procedure. Conclusions: The presented method to select patients for ART pre-treatment reduces the labour of ART, contributing to a more effective allocation of the department resources.